As more and more consumers rely on electronic online access to information about products for purchase, more and more merchants will need to consider providing electronic access to information about goods and services available to those consumers. In a typical electronic commerce situation, a merchant compiles a database of their products and/or services, possibly including information about each product (size, color, type, description, price, etc.). Then the merchant provides consumers with an external electronic interface to that database, such as through a Web server, giving access to those consumers with Internet connectivity on their computers, computing devices, or telecommunication devices. Consumers can then review the merchant's available offerings, select items of interest, and even order them by interacting with the merchant's interface (e.g., selecting items and quantities, arranging for payment, arranging for delivery, etc.).
Online shopping is more remote and less physical than in-person shopping, as computers and computer displays are limited in what they can provide to the potential consumer. For example, the consumer will not be able to feel, smell, hold or manipulate the actual product being ordered. These shortcomings are not an issue where the consumer knows the product and it is unchanging. For example, when the consumer is ordering a specific book by title known to the consumer or a familiar bag of pet food, all the consumer really needs is minimal information, and possibly a photo of the item, to ensure that they are ordering the specific item they had in mind. However, with some other classes of goods, online ordering has been somewhat limiting.
For example, when ordering items of clothing, online shopping has significant limitations. For one, because consumers rarely buy the exact same article of clothing over and over, they often do not have specific clothing items in mind while shopping, such as a particular brand, size, color, etc. of pants. More typically, a consumer is purchasing some item of clothing he or she does not already have an exact copy of, so there may be a question of how that item might fit and look when worn by that consumer.
With some clothing items, fit can be inferred from a description. For example, the fit for a belt that is 38 inches long and one inch wide might be inferred from that description alone. However, for other items, such as a dress, fit might not be so straightforward and in some cases, the best approach is for the consumer to physically have the item and try it on, which is impossible with online shopping. Another difficulty is the wide variety of clothing items that can include garments, accessories, shoes, belts, etc. The complexity of online shopping is further compounded for the consumer trying to assemble an outfit, that is, a set of two or more clothing items intended to be used or worn together.
A number of approaches have been tried to bridge the gap between online shopping for clothing items and having the item in hand to try on.
One approach is to take measurements from the consumer, assume other measurements, and then custom make the desired clothing item according to tailoring assumptions and/or standard models. Because of the wide variety of human body shapes and garment types this may work well for some people but not others.
Another approach is to have clothing items represented by geometric models: scan an image of the consumer (or the consumer herself), and then use computer graphics techniques to generate a combined image of the consumer and a geometric model of a garment in an attempt to show a simulation of how that consumer might look, if she were actually wearing that garment. Such an approach takes time and might require the consumer to “virtually” try on a great many clothing items—one after another.
Online apparel shopping results in greater percentages of returns compared with purchases made at a physical store. Most of the return rate for women's clothing sold in the U.S. is due to size and fit problems.
One cause of fit problems is a lack of standards. The U.S. Department of Commerce withdrew the commercial standard for the sizing of women's apparel in 1983, and since then clothing manufacturers and retailers have repeatedly redefined the previous standards or invented their own proprietary sizing schemes. The garment size for an individual often differs from one brand of apparel to another and from one style to another. This is commonly seen with women's clothing. A dress labeled “size 10” of a particular style from one manufacturer fits differently than a size 10 from another manufacturer or perhaps even a different style from the same manufacturer. One may fit well, the other not at all. Even within a single size from a single manufacturer, there can be fit problems caused by the wide variation in consumers' body shapes. Consumers typically must try on multiple garments before finding and buying one that fits.
There are more than 5,000 designers and each of them might use a particular body fit model that represents a different body proportion and change these models from season to season and style to style. Thus, what fits changes based on designer, style of garment, season, and can also change with different fabrics and weaves and washes.
The lack of sizing standards combined with unreliable labeling cause apparel fit problems, which in turn cause a very high rate of apparel returns, lost sales, brand dissatisfaction, time wasted in fitting rooms, and intense consumer frustration. The problems are only compounded when consumers attempt to make clothing purchases online instead of trying on actual clothing items in a bricks-and-mortar store.
Another attempt to deal with these problems involves analyzing a wide range of a market population and then designing a range of body shapes and designs for a particular garment based on that population. For example, manufacturers might be directed to produce several shapes of a particular pant to offer different fit choices in pants given what the population for the market for such pants is estimated at. The problem is that this approach still relies on the trial and error of locating that pant and determining individually whether it is a good match.
Improved methods and apparatus are needed.